Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/fikrilal/engineering-agent-skills/write-engineering-proposalnpx skills add fikrilal/engineering-agent-skills --skill write-engineering-proposalgit clone --depth 1 https://github.com/fikrilal/engineering-agent-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/fikrilal/engineering-agent-skills/write-engineering-proposal)<a href="https://agentmods.dev/skills/fikrilal/engineering-agent-skills/write-engineering-proposal"><img src="https://agentmods.dev/badge/skills/fikrilal/engineering-agent-skills/write-engineering-proposal.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00071 | $0.01146 |
| Opus 5 | $0.00036 | $0.00573 |
| Sonnet 5 | $0.00014 | $0.00229 |
| Haiku 4.5 | $0.00007 | $0.00115 |
Grade A, and why
write-engineering-proposal scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 109 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Write Engineering Proposal
Turn settled discussion into a decision-ready engineering document grounded in the current codebase. Adapt the document to the change; do not force every proposal through the same headings.
Read references/proposal-boundaries.md before starting.
Workflow
1. Recover the decision context
Extract from the conversation:
- the problem and desired outcome;
- decisions already accepted;
- rejected approaches and reasons;
- constraints, invariants, and non-goals;
- unresolved questions.
Do not reopen settled decisions without new repository evidence. Ask only when a missing decision blocks a coherent proposal; otherwise record it as an open question with a recommended default.
2. Ground the proposal in the repository
Read repository instructions first, then locate product, architecture, engineering, security, testing, release, and planning sources relevant to the change. Inspect actual entry points, composition, contracts, state ownership, persistence, and tests.
Search for existing proposals, ADRs, and execution-plan conventions. Reuse repository terminology and destination conventions. If no document convention exists, ask whether the user wants a file or an in-chat draft before creating a new documentation hierarchy.
3. Classify engineering concerns
Select every material lens and read only its reference:
| Concern | Trigger | Reference |
|---|---|---|
| Desktop/platform | Native APIs, tray/menu-bar, Tauri/Electron, OS lifecycle, packaging | references/desktop-platform.md |
| Mobile/platform | Android/iOS lifecycle, permissions, background work, device capabilities | references/mobile-platform.md |
| API/distributed systems | HTTP/RPC, remote services, queues, retries, contracts | references/api-distributed-systems.md |
| Data/persistence/sync | Databases, migrations, caches, offline data, synchronization | references/data-persistence-sync.md |
| Security/privacy | Identity, auth, secrets, sensitive data, trust boundaries | references/security-privacy.md |
| UI/product state | User workflows, navigation, state ownership, accessibility | references/ui-product-state.md |
| Background processing | Schedulers, workers, long-running tasks, concurrency | references/background-processing.md |
| Local ingestion | Files, local databases, external-tool artifacts, incremental collection | references/local-ingestion.md |
| Delivery/operations | CI, deployment, packaging, updates, rollback, runtime proof | references/delivery-operations.md |
What ships with it
11 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- references/api-distributed-systems.md 1.0 KB
- references/background-processing.md 983 B
- references/data-persistence-sync.md 1016 B
- references/delivery-operations.md 1.2 KB
- references/desktop-platform.md 1.2 KB
- references/diagram-guidance.md 2.3 KB
- references/local-ingestion.md 1.2 KB
- references/mobile-platform.md 994 B
- references/proposal-boundaries.md 1.3 KB
- references/security-privacy.md 1.1 KB
- references/ui-product-state.md 1.0 KB
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 4d ago First seen · 109 lines · 71 tokens per session scan A 9b055c16094e
write-engineering-proposal is a skill published in the GitHub repository fikrilal/engineering-agent-skills (2 stars, last pushed 1mo ago), licensed MIT. It adds 71 tokens to every session and 1,146 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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